Can you learn Data Science and Machine Learning in 30 Days.
Published Nov 14 2022 08:37 AM 3,170 Views


On 17th October, we embarked on a #30DaysOfDataScience journey, going from understanding the Python language to working with real life data and finally creating Machine Learning models both on Azure and in Python. Using the knowledge gained we were able to make decisions such as fraud detection, customer segmentation and salary prediction. Therefore, yes, you can learn Data Science in 30 Days! 


Get Started with the week-by-week roadmap and skills challenge 

Roadmap: The 30Days Skilling content provides a guided tour of Data Science and Machine Learning in Python and Azure in four themed weeks. Explore the roadmap here. 

Gear up: You need to set up your Local Environment ready to get started. Learn how to do this for free here 

Join the Challenge Today: Don't be left behind in the learning, this Cloud Skills Challenge contains modules that will give you skills to successfully get started with Python and Azure. The challenge closes on 30th November, 2022. 


Watch Recordings of our Live sessions 

Session Title 


Live Link 

Setting up your Local Python Environment 

Oluseye Jeremiah 

Watch Recording 

Create your first program with Python 

Odion Sonny-Egbeahie 

Watch Recording 

Data Wrangling and Manipulation 

Korey Stegared-Pace 

Watch Recording 

Data Visualization 

Victor Mureithi 

Watch Recording 

Build a salary predictor model 

Pamela Fox 

Watch Recording 

Build a fraud detecting model - classification 

Raheem Nasirudeen 

Watch Recording 

Build a customer segmentation model - clustering 

Carlotta Castellucio 

Watch Recording 

Curate your Data Science Portfolio 

Anna Wykes, Bunmi Akinremi 

Watch Recording 

Next Steps... 

Once you go through the resources, get started on the capstone project. Capstone Project: Building a recommender System and deploying it to Microsoft Azure. Below are resources you might need for the project: 


Submit your here project by 30th November. 

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‎Nov 16 2022 06:08 AM
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